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Inventory Management Techniques and Technologies that Can Effectively Reduce Defects Per Million Opportunities in Indian Ecommerce
Vikas Bajpai
UNDER THE GUIDANCE OF Prof. Ilyas Khan
MASTER OF BUSINESS ADMINISTRATION
SCHOOL OF BUSINESS
GALGOTIAS UNIVERSITY
ABSTRACT
The current research aims to explore the critical role of inventory management techniques and advanced technologies in reducing defects per million opportunities (DPMO) within the rapidly growing Indian e-commerce sector. In light of the increasing market competition and heightened consumer expectations of the industry, it becomes vital to mitigate discrepancies associated with inventory to ensure operational excellence, reduce costs, and enhance customer satisfaction. this research systematically investigates a range of inventory management strategies, including technological automation through centralized warehouse coordination systems (WMS), sophisticated anticipatory demand estimation models leveraging artificial intelligence (AI) and machine learning, lean inventory methodologies, and quality management frameworks such as Six Sigma. Utilizing an exploratory research design, data were collected from multiple secondary sources, including company websites, industry reports, and documented case studies of leading e-commerce players like Amazon India, Flipkart, BigBasket, Myntra, and Nykaa. Qualitative and quantitative analyses were conducted to assess how these companies implement various inventory management practices and their impact on reducing defect rates.
The results indicate that companies incorporating integrated automated systems achieve higher inventory accuracy and lower DPMO, directly contributing to improved order fulfillment rates and reduced return and cancellation rates. anticipatory demand estimation powered by data analytics emerged as a key enabler in maintaining optimal stock levels, preventing both stockouts and overstocking that typically cause defects. Lean methodologies and real-time replenishment strategies (JIT) inventory management further complement technological interventions by streamlining inventory flow, minimizing waste, and reducing error opportunities. this research concludes that a holistic approach combining technology adoption, data-driven decision-making, and process optimization is most effective in defect reduction. Based on these insights, the thesis recommends Indian e-commerce firms invest strategically in end-to-end automated inventory management systems, enhance their analytics capabilities for precise anticipatory demand estimation, and adopt continuous improvement frameworks such as Six Sigma to sustain defect minimization efforts. this research contributes to the body of knowledge on supply chain excellence in emerging markets and provides actionable guidance for practitioners aiming to elevate inventory management performance.